JP2009297382A - Brain activity information output device and brain activity information power output method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To solve such a problem that a conventional device has never output high-precision brain activity information. <P>SOLUTION: The brain activity information output device comprises a brain activity information acquisition part to estimate and acquire brain activity information as information of brain activity using measured brain signal information and advance brain information, an artifact information acquisition part to estimate and acquire one or more pieces of artifact information as information of an artifact source using the measured brain signal information and one or more pieces of advance artifact information, an output brain activity information acquisition part to remove any effect of an artifact from the measured brain signal information and to acquire output brain activity information as output information of the brain activity using the measured brain signal information, the brain activity information, and one or more pieces of artifact information, and an output part to output the output brain activity information, which realizes the high-precision brain activity information output. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a brain activity information output device that outputs brain activity information that is a brain activity signal.

  Conventionally, an artifact removal method that removes EEG or MEG artifacts by a statistical method using principal component analysis or independent component analysis has been proposed. However, this method is not an effective method because there is a fear that even the brain activity having the waveform similar to the artifact may be removed, the component of the brain activity may be removed. Artifacts are so-called noise.

In addition, a method has been proposed in which an artifact is removed by placing a dipole on an artifact source (eyeball) and subtracting it from the EEG (Non-Patent Document 1). The artifact source is a so-called noise source.
P. Berg and M. Scherg, Electroencephalogr Clin. Neurophysiol., 79, 1, pp. 36-44 (1991).

  However, in the method in Non-Patent Document 1, since the observed value includes not only the artifact but also the brain activity, there is a possibility of removing necessary components from the observed value, and highly accurate brain activity information is acquired. could not.

  The brain activity information output device according to the first aspect of the present invention includes a measurement brain signal information storage unit that can store measurement brain signal information that is information related to a measured brain signal, and brain advance information that is information related to brain activity in advance. A brain advance information storage unit that can store information, an artifact advance information storage unit that can store one or more pieces of artifact advance information that is advance information related to an artifact source, the measured brain signal information, and the brain advance information One or more pieces of artifact source information using a brain activity information acquisition unit that estimates and acquires brain activity information that is information of brain activity, the measured brain signal information, and the one or more artifact prior information. Using the artifact information acquisition unit that estimates and acquires the artifact information, the measured brain signal information, the brain activity information, and the one or more artifact information, An output brain activity information acquisition unit that performs processing to remove the influence of artifacts from the measured brain signal information and acquires output brain activity information that is information of brain activity to be output; and an output unit that outputs the output brain activity information; Is a brain activity information output device.

  With this configuration, it is possible to remove the influence of artifacts and output highly accurate information on brain activities using prior information of brain activities and artifact sources.

  Further, in the brain activity information output device according to the second aspect of the present invention, in contrast to the first aspect, the artifact advance information storage unit stores a plurality of artifact advance information, and the artifact information acquisition unit includes a plurality of artifact information acquisition units. For each artifact source, the artifact information is estimated, a plurality of artifact information is acquired, and the output brain activity information acquisition unit uses the measured brain signal information, the brain activity information, and the plurality of artifact information, It is a brain activity information output device that performs processing to remove the influence of a plurality of artifacts from the measured brain signal information and obtains output brain activity information that is information of brain activity to be output.

  With this configuration, it is possible to remove the influence of artifacts using brain information and prior information of a plurality of artifact sources, and to output more accurate information on brain activities.

  Further, in the brain activity information output device according to the third aspect of the present invention, the brain prior information and the one or more pieces of artifact prior information are information relating to signal strength, relative to either the first or second aspect of the invention. The brain activity information output device is characterized in that it includes certain intensity information, and the intensity information of the brain prior information is different from the intensity information of the one or more pieces of artifact prior information.

  With this configuration, information on brain activity and artifact sources is output in advance, and information about the intensity of the signal, which is information related to signal strength, is used to remove the effects of artifacts and output more accurate information on brain activity. it can.

  Further, in the brain activity information output device according to the fourth aspect of the present invention, with respect to any one of the first to third aspects, the one or more artifact prior information is prior information related to an artifact source included in the living body of the subject. It is a brain activity information output device including certain biological artifact prior information.

  With such a configuration, it is possible to remove the influence of artifacts and output highly accurate information on brain activities using brain information and prior information on artifact sources included in the living body.

  Further, in the brain activity information output device according to the fifth aspect of the invention, in contrast to the fourth aspect of the invention, the one or more artifact advance information is an external artifact that is advance information relating to an external artifact source that is not included in the living body of the subject. It is a brain activity information output device including prior information.

  With this configuration, it is possible to remove the influence of artifacts and output highly accurate information on brain activities using prior information of brain activities and in vitro artifact sources.

  Further, in the brain activity information output device according to the sixth aspect of the present invention, in contrast to any one of the first to fifth aspects, the brain prior information represents fMRI intensity information as current distribution and represents prior knowledge about the current distribution. Each of the one or more artifact prior information is a prior distribution that uses a large current dispersion as compared to the fMRI intensity information and represents prior knowledge about the current distribution, and the brain activity information acquisition unit includes: Brain activity information, which is information about current at a plurality of dipole positions, is estimated and acquired using hierarchical Bayesian estimation using the measured brain signal information and the brain prior information, and the artifact information acquisition unit includes: One or more artifact information, which is information about the current at the dipole position of the artifact source, includes the measured brain signal information and the one or more artifact prior information. The output brain activity information acquisition unit is arranged at a position considered to have no brain activity in the brain activity information from the measured brain signal information. The brain activity information output device obtains output brain activity information by performing a process excluding the brain activity information corresponding to the dipole and the artifact information.

  With such a configuration, information on brain activity can be estimated at the current level.

  Further, in the brain activity information output device according to the seventh aspect of the present invention, the measured brain signal information is information relating to a magnetic field observed around the head, and the output The brain activity information acquisition unit obtains background brain magnetic field information, which is information related to a magnetic field, from current information, which is brain activity information corresponding to a dipole arranged at a position considered to have no brain activity in the brain activity information. Obtaining and obtaining the artifact magnetic field information that is information about the magnetic field from the information of the current that is the artifact information, performing the process of removing the background brain magnetic field information and the artifact magnetic field information from the measured brain signal information, It is a brain activity information output device that acquires output brain activity information.

  With such a configuration, it can be estimated at the sensor level.

  The brain activity information output device according to the eighth aspect of the present invention provides the output brain activity information acquired by the output brain activity information acquisition unit, the measured brain signal information, And a noise removal accuracy information acquisition unit for acquiring noise removal accuracy information, which is information related to noise removal accuracy in the output brain activity information, and the output unit stores the noise removal accuracy information in advance. The brain activity information output device outputs the output brain activity information only when the accuracy is higher than the threshold value.

  With this configuration, it is possible to output information on brain activity after confirming that the accuracy is above a certain level.

  According to the brain activity information output device according to the present invention, it is possible to remove the influence of artifacts using brain information and prior information on artifact sources, and to output highly accurate information on brain activities.

Hereinafter, embodiments of a brain activity information output device and the like according to the present invention will be described with reference to the drawings. In addition, since the component which attached | subjected the same code | symbol in embodiment performs the same operation | movement, description may be abbreviate | omitted again.
(Embodiment 1)

  In the present embodiment, a brain activity information output system capable of removing the influence of artifacts and outputting highly accurate information on brain activities using prior information of brain activities and artifact sources will be described. Further, in the present embodiment, a brain activity information output system that estimates brain activity information based on current levels will be described. In the present embodiment, a case where there are a plurality of artifact sources will be described. In addition, in this embodiment, a brain activity information output system that assumes that the signal magnitudes of the brain prior information and the artifact prior information are different will be described. The artifact source may be a living eyeball, heart, myoelectricity, or the like, or an external source such as TV radio waves. Furthermore, in this embodiment, after checking the brain activity signal and confirming that the accuracy is above a certain level, the output of the brain signal will be described. Note that artifact prior information has the same meaning as noise prior information.

  FIG. 1 is a block diagram of a brain activity information output system in the present embodiment. The brain activity information output system includes a brain signal measurement device 11 and a brain activity information output device 12.

  The brain signal measuring device 11 is a device that measures brain signals. The brain signal measuring device 11 is, for example, a brain magnetic field measuring device. The magnetoencephalographic measurement apparatus may include a brain cap 1101 as an observation means for observing an event related to brain activity. The brain cap 1101 has, for example, a 208 channel sensor. However, the number of channels of the brain cap 1101 does not matter. The brain signal may be a magnetic field or an electric current.

  The brain activity information output device 12 includes a measured brain signal information storage unit 121, a brain advance information storage unit 122, an artifact advance information storage unit 123, a brain activity information acquisition unit 124, an artifact information acquisition unit 125, and an output brain activity information acquisition unit 126. , A noise removal accuracy information acquisition unit 127 and an output unit 128 are provided.

  The brain activity information output device 12 is a device that removes artifacts from measured brain signal information, which is information related to brain signals acquired by the brain signal measurement device 11, and outputs highly accurate brain activity information.

  The measured brain signal information storage unit 121 can store measured brain signal information that is information related to the measured brain signals. The measured brain signal information may be a measurement result of a magnetoencephalogram measurement device (an example of the brain signal measurement device 11), or may be information obtained by removing low-frequency drift from the measurement result. The measured brain signal information may be MEG data or current information. In addition, usually, the measured brain signal information is information of a plurality of points (for example, 208 channels), and the measured brain signal information storage unit 121 stores a plurality of brain signal information.

The measured brain signal information is, for example, a weak magnetic field observed around the head of the subject with an electrical change in the subject's cranial nerve activity. For example, a neural current is modeled by N current dipoles whose positions and directions are fixed, and the magnetic field observed on M MEG sensors, whose intensity is represented by an N-dimensional vector J, is represented by an M-dimensional vector B. And the following equation holds.

  This M-dimensional vector B is an example of measured brain signal information. The N-dimensional vector J may be used as an example of measured brain signal information. Here, G is called a lead field matrix and is a matrix representing a magnetic field generated by a unit current moment. Assuming that the inside of the skull surrounding the brain is a uniform medium sphere, the lead field component can be analytically calculated by the Sarvas equation. Assume that a current dipole with a perpendicular orientation on the cortical surface is assumed based on the knowledge that the main brain activity component that generates the MEG signal is the current flowing in the cone cells. The Sarvas equation is a well-known equation and will not be described in detail.

  The measurement brain signal information storage unit 121 is preferably a non-volatile recording medium, but can also be realized by a volatile recording medium. The process in which the measurement brain signal information is stored in the measurement brain signal information storage unit 121 does not matter. For example, the measurement brain signal information may be stored in the measurement brain signal information storage unit 121 via a recording medium, and the measurement brain signal information transmitted from the brain signal measurement device 11 via a communication line or the like is stored. The measurement brain signal information storage unit 121 may store the information, or the measurement brain signal information input via the input device may be stored in the measurement brain signal information storage unit 121. .

The brain advance information storage unit 122 can store brain advance information that is advance information related to brain activity. The brain prior information is a prior distribution with respect to the brain current and is information determined based on prior knowledge. The brain prior information is, for example, P ₀ (J) described later. The prior brain information is derived by deriving means (not shown) using, for example, hierarchical Bayesian estimation. In hierarchical Bayesian estimation, hierarchical prior distributions for the following dipoles are acquired. In addition, it is preferable that the brain prior information includes intensity information that is information related to the intensity of the signal. Further, the brain prior information may be a prior distribution representing fMRI intensity information as current dispersion and representing prior knowledge about the current distribution.

  Hereinafter, a method for estimating a current at a dipole position using hierarchical Bayesian estimation will be described before describing a method for acquiring a hierarchical prior distribution.

That is, the magnetic field measured at the M point near the brain surface is B = (B ₁ ,..., B _M ) ^T , and the current distribution flowing through the dipole assumed on the brain surface is J = {J _i | i = 1. ,..., N}. In the hierarchical Bayesian estimation, it is assumed that the probability P (B | J) that the magnetic field B is observed when the current distribution J is given follows the normal distribution of Equation 2.

In Equation 2, β is the reciprocal of noise variance. Further, the posterior distribution (P (J | B)) of the current J when the magnetic field B is observed is expressed by the following Equation 3.

In Equation 3, P (B) is the marginal likelihood. P ₀ (J) is a prior distribution with respect to the current, and is determined based on predetermined prior knowledge. In hierarchical Bayesian estimation, hierarchical prior distributions for dipoles as shown in the following equations 4 to 6 are introduced.

In Equation 4, A is a diagonal matrix whose diagonal component is α = {α _i | i = 1,..., N}, and α ^{? 1} _i corresponds to the pre-current distribution of J _i . Here, it is assumed that a parameter representing the prior current dispersion is shown in the following Expression 7.

The parameters of the hierarchical prior distribution ν _0i bar (the bar means a character having − on ν) and γ _0i are called _{hyperparameters} . These values are defined from fMRI activity intensity information (t value), magnification parameter m ₀ , and reliability parameter γ ₀ · γ _0i . The ν _0i bar is set in accordance with the fMRI t value, and the ν _0i bar is expressed as in Equation 8 when the background current dispersion is ν _{0, base} . The hyper parameter is an example of intensity information that is information on the intensity of the signal.

Here, t _i hat (hat, it indicates the presence of ^ over t) is the maximum value is a value obtained by normalizing the t value of fMRI to be 1.

If the ν _i bar is large, the probability that the current dispersion becomes large increases (meaning that prior information is given that the current easily flows through the i-th dipole). The _{hyperparameter} γ _0i controls the reliability of the hierarchical prior distribution. The smaller γ _0i is, the lower the reliability is, and the larger γ _0i is, the higher the reliability is.

The prior brain information is information obtained by substituting fMRI activity intensity information into Formula 8 and estimating prior variance as m ₀ = 100 and γ _0i = 100 by a brain prior information acquisition unit (not shown), for example. . The prior brain information is information obtained by estimating prior dispersion for a dipole placed on the cortex.

  The brain prior information storage unit 122 is preferably a non-volatile recording medium, but can also be realized by a volatile recording medium. The process in which brain prior information is stored in the brain prior information storage unit 122 does not matter. For example, the brain advance information may be stored in the brain advance information storage unit 122 via a recording medium, and the brain advance information transmitted via a communication line or the like is stored in the brain advance information storage unit 122. Alternatively, the prior brain information input via the input device may be stored in the prior brain information storage unit 122.

The artifact advance information storage unit 123 may store one or more pieces of artifact advance information that are advance information related to the artifact source. It is preferable that the artifact advance information storage unit 123 stores a plurality of artifact advance information. The artifact source is, for example, an eyeball, a masticatory muscle, a heartbeat, or the like that is a part of a living body. The artifact source may be, for example, a television that is an external artifact source other than a living body, a passage of a transported object (such as an automobile, a truck, or a train). That is, the artifact advance information includes biological artifact advance information that is advance information regarding an artifact source included in the subject's living body. Further, the artifact prior information may include external artifact prior information that is prior information regarding an external artifact source that is not included in the subject's living body. The artifact prior information is information obtained by using hierarchical Bayesian estimation, for example, similarly to the brain prior information, and is a hierarchical prior distribution for dipoles such as Expressions 4 to 6. However, artifact prior information differs from brain prior information in the magnitude of current dispersion (intensity information, which is the intensity of a signal). For example, various types of artifact prior information are expressed as Equations 9 and 10. In addition, it is preferable that the artifact prior information includes strength information. In addition, it is preferable that the intensity information of the brain prior information and the intensity information of the one or more pieces of artifact prior information are different. Furthermore, it is preferable that each artifact prior information is a prior distribution that uses a larger current dispersion than the fMRI intensity information and represents prior knowledge about the current distribution.

Here, the ν _eye bar (the bar indicates that it has − on ν), the ν _cardiac bar, and the ν _statistical bar are _{hyperparameters} ν _0i bar related to the dipole placed at the eyeball center, heart position, and masticatory muscle, respectively. It is. In addition, γ _eye , γ _cardiac , and γ _masicatory represent the same values for the _{hyperparameter} γ _0i .

Note that ν _brain bar: ν _eye bar: ν _cardiac bar: ν _quantitative bar may have a simple ratio such as “1: 50: 5000: 100”, for example.

  In addition, these prior current dispersions are, for example, the first index that is the degree of fit between the observed magnetic field and the restored magnetic field (Goodness-of-fit, GoF) by the artifact prior information acquisition unit (not shown), and fMRI activity intensity information And a second index that is a correlation coefficient of average current dispersion are preferably determined based on two types of indices.

Specifically, GoF is an amount defined by Equation 11.

In Equation 11, the measured magnetic field in channel j is B _obs (j), and the restored magnetic field in channel j is B _est (j). M is the number of sensors. If the magnetic field calculated from the estimated current (restored magnetic field) matches the observed magnetic field, the GoF increases (approaches 100). GoF was used as a judgment material for selecting a hyperparameter that matches the estimation result and the measurement result. As for the second index, it is expected that nerve activity in the brain also increases at a position where fMRI activity is expected. Therefore, it is considered that there is a correspondence between the activity intensity information of fMRI and the average current dispersion (the two correlation coefficients are expected to be the largest). Coarse information on the current intensity of the artifact source is set in advance by selecting a set of hyperparameters that satisfies the conditions of the first index and the second index as much as possible. Artifact prior information) is estimated and acquired. The artifact advance information storage unit 123 is preferably a non-volatile recording medium, but can also be realized by a volatile recording medium. The process in which the artifact advance information is stored in the artifact advance information storage unit 123 does not matter. For example, the artifact advance information may be stored in the artifact advance information storage unit 123 via a recording medium, and the artifact advance information transmitted via a communication line or the like is stored in the artifact advance information storage unit 123. Alternatively, the artifact advance information input via the input device may be stored in the artifact advance information storage unit 123.

The brain activity information acquisition unit 124 uses the measured brain signal information stored in the measured brain signal information storage unit 121 and the brain prior information stored in the brain prior information storage unit 122 as brain activity information. Estimate and obtain certain brain activity information. The brain activity information acquisition unit 124 uses measured brain signal information (for example, B) and brain prior information (for example, P ₀ (J)) as brain activity information that is information about current at a plurality of dipole positions. It is preferable to estimate and obtain using hierarchical Bayesian estimation. For example, the brain activity information acquisition unit 124 stores the information of Formula 3 described above, and acquires the posterior distribution (P (J | B)) of the current J using the Formula 3. The posterior distribution (P (J | B)) of the current J is brain activity information. The brain activity information acquisition unit 124 can usually be realized by an MPU, a memory, or the like. The processing procedure of the brain activity information acquisition unit 124 is usually realized by software, and the software is recorded in a recording medium such as a ROM. However, it may be realized by hardware (dedicated circuit).

  The artifact information acquisition unit 125 estimates and acquires one or more artifact information, which is information of an artifact source, using the measured brain signal information and the one or more artifact prior information. It is preferable that the artifact information acquisition unit 125 estimates the artifact information for each of the plurality of artifact sources and acquires the plurality of artifact information. The artifact information acquisition unit 125 estimates one or more artifact information, which is information about the current at the dipole position of the artifact source, using hierarchical Bayesian estimation using measured brain signal information and one or more artifact prior information. However, it is suitable to acquire. The artifact information acquisition unit 125 performs the same operation as the brain activity information acquisition unit 124, although the prior information is different. That is, the artifact information acquisition unit 125 acquires the posterior distribution (P (J | B)) of the current J corresponding to each artifact source using Equation 3. The artifact information acquisition unit 125 can usually be realized by an MPU, a memory, or the like. The processing procedure of the artifact information acquisition unit 125 is usually realized by software, and the software is recorded on a recording medium such as a ROM. However, it may be realized by hardware (dedicated circuit).

  The output brain activity information acquisition unit 126 performs processing for removing the influence of the artifact from the measured brain signal information using the measured brain signal information, the brain activity information, and one or more artifact information, and outputs the brain activity information as output information. Get some output brain activity information. That is, in order to remove the influence of the artifact, the dipole of the brain cortex and the dipole of the artifact source are simultaneously estimated. The estimation of the dipole of the brain cortex is a process in which the brain activity information acquisition unit 124 acquires brain activity information. The estimation of the artifact source dipole is a process in which the artifact information acquisition unit 125 acquires one or more pieces of artifact information that is information of the artifact source.

  Further, the output brain activity information acquisition unit 126 performs processing for removing the influence of the plurality of artifacts from the measured brain signal information using the measured brain signal information, the brain activity information, and the plurality of artifact information, and is outputted. It is preferable to obtain output brain activity information that is information of the above.

  Further, the output brain activity information acquisition unit 126 removes, from the measured brain signal information, brain activity information and artifact information corresponding to a dipole arranged at a position considered to have no brain activity in the brain activity information. To obtain output brain activity information. Information on dipoles arranged at positions where it is considered that there is no brain activity may be set in advance, or may be given manually by the user.

Hereinafter, a specific operation example of the output brain activity information acquisition unit 126 and the like will be described. If the brain cortex and artifact source dipole are J _brain , J _noise , the lead field matrix is G _brain , G _noise , and the prior dispersion of the dipole is A ^{? 1} _brain , A ^{? 1} _noise , then the following equations 12 to 14 , The brain activity information acquisition unit 124 and the artifact information acquisition unit 125 estimate the brain cortex and the artifact source dipole J, respectively.

That is, after the brain activity information acquisition unit 124 and the artifact information acquisition unit 125 simultaneously estimate the artifact source and the cortical dipole by the hierarchical Bayesian estimation method, the output brain activity information acquisition unit 126 is located at a position where there is no fMRI activity. The magnetic field _generated only by the arranged dipole is removed from the observed magnetic field B according to Equation 15 to calculate B _pruned and placed on the memory. The observed magnetic field B is an example of measured brain signal information, and B _pruned is an example of output brain activity information.

  The output brain activity information acquisition unit 126 can be usually realized by an MPU, a memory, or the like. The processing procedure of the output brain activity information acquisition unit 126 is usually realized by software, and the software is recorded in a recording medium such as a ROM. However, it may be realized by hardware (dedicated circuit).

  The noise removal accuracy information acquisition unit 127 uses the output brain activity information acquired by the output brain activity information acquisition unit 126 and the measured brain signal information, and performs noise removal that is information regarding the accuracy of noise removal in the output brain activity information. Get accuracy information. An example of a specific process of the noise removal accuracy information acquisition unit 127 will be described later. The noise removal accuracy information acquisition unit 127 can be usually realized by an MPU, a memory, or the like. The processing procedure of the noise removal accuracy information acquisition unit 127 is usually realized by software, and the software is recorded in a recording medium such as a ROM. However, it may be realized by hardware (dedicated circuit).

  The output unit 128 outputs output brain activity information. The output unit 128 may output the output brain activity information only when the noise removal accuracy information is higher than the threshold value stored in advance. Here, output refers to display on a display, projection using a projector, printing on a printer, sound output, transmission to an external device, storage in a recording medium, other processing device or other program, etc. It is a concept including delivery of processing results. The output unit 128 may or may not include an output device such as a display or a speaker. The output unit 128 can be realized by output device driver software, or output device driver software and an output device.

  Next, operation | movement of the brain activity information output apparatus 12 which comprises a brain activity information output system is demonstrated using the flowchart of FIG.

  (Step S201) The brain activity information acquisition unit 124 reads the measurement brain signal information from the measurement brain signal information storage unit 121.

  (Step S202) The brain activity information acquisition unit 124 reads the brain advance information from the brain advance information storage unit 122.

  (Step S203) The brain activity information acquisition unit 124 is a mathematical expression stored in advance, and reads a mathematical formula for estimating brain activity information and the like on the memory. Such a mathematical expression is, for example, an expression for realizing hierarchical Bayesian estimation.

  (Step S204) The brain activity information acquisition unit 124 substitutes the measured brain signal information read in Step S201 and the brain prior information read in Step S202 for the formula read in Step S203, and executes the formula. Get brain activity information and place it on memory.

  (Step S205) The artifact information acquisition unit 125 substitutes 1 for the counter i.

  (Step S206) The artifact information acquisition unit 125 determines whether or not the i th artifact prior information exists in the artifact prior information storage unit 123. If the i th artifact prior information exists, the process proceeds to step S207, and if not, the process proceeds to step S210.

  (Step S207) The artifact information acquisition unit 125 reads the i-th artifact advance information from the artifact advance information storage unit 123.

  (Step S208) The artifact information acquisition unit 125 substitutes the measured brain signal information read in step S201 and the artifact prior information read in step S207 for the mathematical formula read on the memory in step S203, and Execute the formula to get the artifact information and place it in memory.

  (Step S209) The artifact information acquisition unit 125 increments the counter i by 1, and returns to step S206.

  (Step S210) The output brain activity information acquisition unit 126 removes information on a dipole at a position where there is no fMRI activity from the brain activity information acquired in step S204.

  (Step S211) The output brain activity information acquisition unit 126 removes one or more artifact information acquired in Step S208 from the information remaining in Step S210. Then, the output brain activity information acquisition unit 126 obtains output brain activity information.

  (Step S212) The output unit 128 outputs the output brain activity information acquired in step S211 and ends the process.

  In the flowchart of FIG. 2, the order and timing of the processing in step S210 and step S211 are not limited. The processing in step S210 and step S211 is performed using, for example, Equation 15 described above.

  In the flowchart of FIG. 2, the process of the noise removal accuracy information acquisition unit 127 is not performed. However, in the flowchart of FIG. 2, the output unit 128 may output the output brain activity information only when the noise removal accuracy information is higher than the threshold value stored in advance.

  Hereinafter, experimental results using the brain activity information output system in the present embodiment will be described. The test subjects were three healthy men with normal vision. Three subjects (X, Y, Z) participated in both the MEG measurement experiment and the fMRI measurement experiment. Prior to the experiment, the test subject was explained to the subject and the experiment was conducted after obtaining consent.

  The MEG measurement experiment is the following experiment. The brain signal measuring device 11 is a commercially available magnetoencephalographic measuring device having a full-head 208 channel sensor. The brain signal measuring device 11 recorded MEG data at 1000 Hz. MEG data is also considered to be an example of measured brain signal information.

  Then, as an experimental task, the subject performed a task of following the moving target while gazing at the fixed viewpoint (cover pursuit task). Specifically, the task was accomplished in the following flow (a) to (d).

  (A) When the subject is ready, he presses the button to start the task. (B) The fixation point and the target appear in the center of the screen (wait for 1000 ± 500 ms). The target is stationary at the center of the screen. Subject was instructed to continue staring at the fixation point. The time to stare was 4000 ms (pretrigger period). (C) Thereafter, the visual target starts to move in the horizontal direction. The subject was instructed to follow the target in his / her heart while gazing at the fixed viewpoint. The target continued to move for 4000 ms. (D) The target disappears and the subject takes a break. The flow from (a) to (d) was taken as one trial. There were three types of index movement patterns, and 30 trials were presented at random (3 types x 30 trials = 90 trials in total). With this as one session, the subjects performed a total of 3 sessions (1 session 90 trials × 3 sessions = total 270 trials).

  Next, an fMRI measurement experiment will be described. A commercially available 1.5T MRI scanner was used for fMRI measurement. Visual stimuli were presented on a screen placed 370 mm away from the front of the eye. The test subject repeated a test block that follows the sine wave movement mentally without moving his eyes and a control block that keeps a close eye on the stationary fixation point for 18 seconds each. The index of the test block was a red point with a sinusoidal motion having an amplitude of 4 deg and a frequency of 0.5 Hz.

  First, the brain signal measurement device 11 measures and acquires the obtained MEG data by using a reference sensor value and low-frequency drift by low-frequency drift removal means (which the brain signal measurement device 11 has) (not shown). The effect of was removed. Next, data extraction unit (not shown) (which the brain signal measurement device 11 has) cut out data of −400 to +4000 ms with reference to the presentation time of the index, and made this data for one trial. The first 400 ms of the MEG data cut out by the data cutout means is in a state before the index starts moving (pretrigger period), and the mean value of this period is obtained by a correction means (not shown) included in the brain signal measuring device 11. Was used to correct the baseline. The preprocessed MEG data is an example of measured brain signal information stored in the measured brain signal information storage unit 121, and is used for current estimation described later.

  In the analysis, data that affected blinking during task execution was excluded. We also excluded data from sessions in which subjects fell asleep during the experiment. Therefore, among the data measured from subjects X, Y, and Z, 53.3%, 93.0%, and 76.3% data were used for analysis, respectively.

  The analysis of fMRI data was performed using SPM5 (The Wellcome Department of Cognitive Neurology). A test of significant difference in brain activity under the condition that only a stationary fixation point is presented and the eye is gazing at it and the indicator that moves in the upper side while gazing at the fixation point is t The test was conducted.

  A cerebral surface model was created using Brain Voyager (Brain Innovation) based on the MRI structure image of the subject measured in advance. On the whole brain model, 1886 subjects X, 3229 subjects Y, and 2789 dipoles were placed on subject Z. At this time, the dipole was arranged so that a region where brain activity related to the task was expected (significant difference of t test with fMRI was p <0.01 [uncorrected]) was dense. As a result, dipoles are arranged at intervals of 2.15 ± 1.31 (mean ± SD) [mm] in areas where fMRI activity is expected, and 3.91 ± 3.19 [mm] in other areas. It was done.

  In this experiment, we assumed near eyeballs, masticatory muscles, and heartbeats as main artifact sources, and assumed dipoles at each location. The center position of the eyeball and the position of the masticatory muscle were determined from the MRI structure image, and one dipole was placed on each of the left and right. The position of the heart is considered to be a coordinate system in which the anterior commissure (AC) is the origin and the line connecting the anterior commissure and the postcommissure (PC) is the y-axis (the x-axis is perpendicular to the mid-sagittal plane) Left and right direction, z axis is vertical direction perpendicular to these), (x, y, z) = (− 5, 0, −23) [cm].

  When performing current estimation from the MEG data stored in the measured brain signal information storage unit 121 by the hierarchical Bayesian estimation described above, the fMRI activity intensity information (t value) was used as prior knowledge of the hierarchical Bayesian estimation. That is, the brain prior information storage unit 122 stores brain prior information including fMRI activity intensity information (t value). The artifact prior information storage unit 123 stores three pieces of artifact prior information (corresponding to the vicinity of the eyeball, the masticatory muscles, and the heartbeat) including fMRI activity intensity information (t value). At this time, the prior distribution was not given only to the region related to the cover purge task, but the prior distribution was set based on the activity intensity information obtained by the fMRI analysis.

  As described above, the information is stored in the measured brain signal information storage unit 121, the brain advance information storage unit 122, and the artifact advance information storage unit 123.

  Next, the output brain activity information acquisition unit 126 and the like performed the artifact removal as described above using Expressions 12 to 15. Then, for example, the data from which artifacts have been removed by a smoothing unit (not shown) is subjected to a moving average with a time width of 100 ms to smooth the data.

In this experiment, PCA was applied to the measured MEG data to visually confirm that the first main component was similar to the MCG (magnetocardiogram) waveform, and then the component was removed. PCA is principal component analysis.
(Experimental result 1)

  The brain activity information output device 12 predicts the brain activity and the behavior of the artifact at the same time, and performs noise removal. In order to examine the accuracy, a MEG measurement experiment involving a subject was performed. The subject was instructed to execute the task of mentally following the moving target presented in front of the eyes, and the MEG at that time was measured by the brain signal measuring device 11.

  When performing such tasks, MEG data is affected by heartbeat, eyeball artifacts, and muscle activity. Therefore, dipoles were placed on the artifact sources and the surface of the cerebral cortex, and an attempt was made to estimate their currents using the brain activity information output device 12. At that time, considering the fact that the signal sources of the artifact source and the brain activity are different as described above, information relating to the signal intensity is used as prior knowledge in the brain advance information storage unit 122 or the artifact advance information storage unit 123 individually. The output brain activity information acquisition unit 126 estimated the current. Then, the artifact information acquisition unit 125 restores the artifact magnetic field from the estimated current, and the output brain activity information acquisition unit 126 performs artifact removal by subtracting the artifact magnetic field from the measurement data to acquire output brain activity information. did.

  3A shows what time waveform the MEG data becomes at which position of the head. Before the artifact is removed, the waveform is disturbed near the outside of the head and near the eyeball. However, the disturbance is reduced after artifact removal (B in FIG. 3). Further, although the influence of the artifact is expected to be smaller in the vicinity of the center of the head than in the outer portion, the characteristics of the waveform did not change before and after noise removal in such a portion (C in FIG. 3).

Next, the noise removal accuracy information acquisition unit 127 detects a deviation between the noise-removed data and a true value (which reflects only brain activity) as follows, for example. That is, by averaging the measured data over the entire trial, it is possible to suppress the influence of components not related to the task. The noise removal accuracy information acquisition unit 127 assumes that this value is a true value and detects how much deviation has occurred from the value. Specifically, the noise removal accuracy information acquisition unit 127 calculates RMSE (root mean square error) at each sensor of measurement data, data cleaned by PCA, and VBMEG, using Equation 16 below. VBMEG is software for performing hierarchical Bayesian estimation.

  In Equation 16, B is MEG data for a single trial, and B hat (hat is ^ on B) represents the trial average of B. In Equation 16, T represents the number of samples and K represents the number of trials. FIG. 4 shows a calculation result using Expression 16 performed by the noise removal accuracy information acquisition unit 127. 4A to 4C are diagrams in which the trial average value of the RMSE of the target pattern 1 of a typical subject is displayed on the head map.

  The measurement data (A in FIG. 4) and PCA (B in FIG. 4) show the effect of artifacts coming from the outside of the head, but the method using the expansion dipole in the brain activity information output device 12 has a small effect. (C in FIG. 4).

  FIG. 4D is a diagram in which the RMSE of the sensor in the outer peripheral portion (71 pieces) of the head is compared with the observed value and the size of the RMSE by a method using PCA and VBMEG. When analysis of variance was performed for the three analysis methods, a significant difference was found (F (2,638) = 762.61). When multiple comparison (Tukey's HSD test) is performed, there is a significant difference between all data groups ([Observed]-[PCA]: p <0.01, [Observed]-[VBMEG]: p <0. 01, [PCA]-[VBMEG]: p <0.01), and RMSE was the smallest when artifact removal was performed using VBMEG (D in FIG. 4).

From the above, it can be seen that the brain activity information output device 12 was able to better remove the influence of artifacts from the outside of the head.
(Experimental result 2)

  Experimental result 2 shows that artifact removal is performed at the current level estimated at the lattice points in the brain, and the output brain activity information shows that the estimation accuracy is improved at the current level.

  FIG. 5 shows a temporal / spatial pattern of an estimated current waveform when the target is mentally followed (an example of a typical test result of a typical subject). F in FIG. 5 is a time pattern of the target position. FIG. 5A shows a time waveform when a current is estimated by arranging a dipole only on the brain surface. FIG. 5B shows an estimated current waveform when a dipole is also arranged in an assumed artifact source and the brain activity and the behavior of the artifact source are estimated simultaneously. And the spatial pattern of the average electric current dispersion | distribution in the time of a gray area | region is shown to C and D of FIG.

  5C to 5E show estimated current waveforms of dipoles arranged at the artifact source. FIG. 5D relates to a heart dipole, but a waveform having characteristics resembling a heartbeat was obtained. If the estimated current in the brain is greatly distorted by the artifact, it is considered that there is some correlation between the estimated current in the brain and the artifact. However, in the brain current, the correlation between the estimated current at the dipole placed at the artifact source and the brain current (Lateral Octopitial Temporal Cortex, LOTC) was small (correlation coefficient was obtained for each subject, and the average of all subjects was calculated. Values and standard deviations are [eye (left)]: (rx, ry, rz) = (0.00 ± 0.07, 0.00 ± 0.07, 0.02 ± 0.08), [eye ( right)]: (rx, ry, rz) = (0.00 ± 0.08, 0.00 ± 0.00, 0.0 ± 0.00), [cardiac]: (rx, ry, rz) = (0.00 ± 0.08, 0.00 ± 0.08, 0.00 ± 0.07), [masticatory muscle (left)]: (rx, ry, rz) = (0.00 ± 0.07 , 0.0 ± 0.08, 0.00 ± 0.07)), [masticatory muscle (right)]: (rx, ry, rz) = (0.00 ± 0.07, 0.01 ± 0.07, 0. 00 ± 0.08)). It is unlikely that the estimated brain current is distorted by artifacts.

The estimation results were compared between when the dipole was placed only on the brain surface and when the dipole was placed on the artifact source and the brain surface. First, regarding the magnetic field, the degree of fit (GoF) expressed by Equation 17 for the measurement magnetic field and the restoration magnetic field was examined.

  As a result of comparing the GoF obtained under the two conditions, the GoF is significantly increased by placing the dipole in the artifact source (paired t-test (8) = 15.32, p <0.000001, FIG. 5F). The value improved by 12.72 ± 2.35%. The number of dipoles arranged on the surface of the brain is as large as 1886 to 3229, whereas the number of dipoles added to the artifact source is only 15 ([5 artifact sources] × [3 axis directions]). . Although small in number, GoF could be effectively improved by proper placement in the artifact source.

  Next, regarding the estimated current, the estimated current is expected to increase at a position where activity is expected by fMRI. Therefore, the correlation between the fMRI activity intensity information and the average current dispersion of the estimated current was examined. As a result, by placing an extended dipole, the correlation is significantly increased (paired t-test (8) = 2.28, p <0.05, FIG. 6B), and fMRI activity intensity information and average current dispersion There was also an improvement in correlation.

  As described above, according to the brain activity information output device 12 in the present embodiment, it is possible to simultaneously predict the brain activity and the behavior of the artifact and perform noise removal. Therefore, it is possible to output highly accurate information on brain activity.

  In addition, according to the present embodiment, considering the fact that the signal sources of artifact sources and brain activity are different from each other, the information regarding the signal strength is individually set as prior knowledge, and the current is estimated, thereby making the accuracy more accurate. High brain activity information can be output.

Further, according to the present embodiment, artifact magnetic field can be removed by restoring the magnetic field of the artifact from the estimated current and subtracting it from the measured brain signal information, so that highly accurate information on the brain activity can be output.
Further, according to the present embodiment, the measured brain signal information is mainly a magnetoencephalogram (MEG). However, it goes without saying that the measured brain signal information may be an electroencephalogram (EEG). The same applies to other embodiments.

  Furthermore, according to the present embodiment, artifact removal is performed using an extended dipole, and noise can be removed at a sensor level reasonably and effectively compared to the conventional method. In addition, the current level can be cleaned by estimating the brain current including artifacts. Therefore, it is possible to output highly accurate information on brain activity.

  In the present embodiment, the above-described mathematical formula information is normally held in advance by a unit, means, or the like that uses the mathematical formula, and the mathematical formula is read and executed.

  Furthermore, the processing in the present embodiment may be realized by software. Then, this software may be distributed by software download or the like. Further, this software may be recorded and distributed on a recording medium such as a CD-ROM. This also applies to other embodiments in this specification. Note that the software that realizes the brain activity information output apparatus according to the present embodiment is the following program. In other words, this program uses a measured brain signal information and brain prior information stored in a storage medium to estimate and acquire brain activity information, which is brain activity information, and Using the measured brain signal information and one or more artifact prior information stored in a storage medium, estimating and acquiring one or more artifact information that is information of an artifact source; and Using the measured brain signal information, the brain activity information, and the one or more artifact information, a process for removing the influence of the artifact from the measured brain signal information is performed, and output brain activity information that is information of the brain activity to be output is obtained. It is the program for functioning as an output brain activity information acquisition part to acquire, and an output part which outputs the output brain activity information.

  In the program, the artifact information acquisition unit estimates artifact information for each of a plurality of artifact sources, acquires a plurality of artifact information, and the output brain activity information acquisition unit includes the measured brain signal information and the Using brain activity information and the plurality of artifact information, processing to remove the influence of the plurality of artifacts from the measured brain signal information, so as to obtain output brain activity information that is information of the brain activity to be output, A program for causing a computer to function is suitable.

  In the above program, the brain prior information and the one or more pieces of artifact advance information include intensity information that is information related to the strength of the signal, and the intensity information of the brain prior information and the one or more pieces of artifact advance information. It is preferable that each intensity information of information is different.

  In the above program, it is preferable that the one or more artifact advance information includes biological artifact advance information that is advance information related to an artifact source included in the living body of the subject.

  In the above program, it is preferable that the one or more artifact prior information includes external artifact prior information that is prior information related to an external artifact source that is not included in the subject's living body.

  Further, in the above program, the brain prior information is a prior distribution representing fMRI intensity information as current dispersion and representing prior knowledge about the current distribution, and each of the one or more artifact prior information is compared with the fMRI intensity information. The brain activity information acquisition unit uses a large current dispersion and represents prior knowledge about the current distribution, and the brain activity information acquisition unit converts brain activity information, which is information about currents at a plurality of dipole positions, into the measured brain signal information. And the artifact information acquisition unit obtains one or more pieces of artifact information, which is information about the current at the dipole position of the artifact source, from the measurement. Estimating and obtaining using hierarchical Bayesian estimation using brain signal information and the one or more artifact prior information, The output brain activity information acquisition unit excludes, from the measured brain signal information, brain activity information corresponding to a dipole arranged at a position considered to have no brain activity in the brain activity information and the artifact information It is preferable that the program is a program for causing a computer to function so as to perform processing and acquire output brain activity information.

  In the above program, the measured brain signal information is information related to a magnetic field observed around the head, and the output brain activity information acquisition unit is considered to have no brain activity in the brain activity information. The background brain magnetic field information, which is information on the magnetic field, is acquired from the information on the current corresponding to the brain activity information corresponding to the dipole placed at the position, and the artifact magnetic field information, which is information on the magnetic field, from the information on the current, which is the artifact information. And a program for causing the computer to function so as to obtain the output brain activity information by performing a process of removing the background brain magnetic field information and the artifact magnetic field information from the measured brain signal information. Is preferred.

  Furthermore, in the above program, noise removal accuracy information that is information relating to noise removal accuracy in the output brain activity information using the output brain activity information acquired by the output brain activity information acquisition unit and the measured brain signal information The output unit outputs the output brain activity information only when the noise removal accuracy information is higher in accuracy than a threshold value stored in advance. Thus, it is preferable that the program is a program for causing a computer to function.

  FIG. 7 shows the external appearance of a computer that executes the program described in this specification to realize the brain activity information output device and the like of the above-described embodiment. The above-described embodiments can be realized by computer hardware and a computer program executed thereon. FIG. 7 is an overview diagram of the computer system 340, and FIG. 8 is a block diagram of the computer system 340.

  In FIG. 7, the computer system 340 includes a computer 341 including an FD drive 3411 and a CD-ROM drive 3412, a keyboard 342, a mouse 343, and a monitor 344.

  In FIG. 8, in addition to the FD drive 3411 and the CD-ROM drive 3412, the computer 341 stores an MPU 3413, a bus 3414 connected to the CD-ROM drive 3412 and the FD drive 3411, and a program such as a bootup program. ROM 3415 for connection, MPU 3413, RAM 3416 for temporarily storing application program instructions and providing a temporary storage space, and hard disk 3417 for storing application programs, system programs, and data . Although not shown here, the computer 341 may further include a network card that provides connection to the LAN.

  A program that causes the computer system 340 to execute functions such as the brain activity information output device of the above-described embodiment is stored in the CD-ROM 3501 or FD 3502, inserted into the CD-ROM drive 3412 or FD drive 3411, and It may be transferred to the hard disk 3417. Alternatively, the program may be transmitted to the computer 341 via a network (not shown) and stored in the hard disk 3417. The program is loaded into the RAM 3416 at the time of execution. The program may be loaded directly from the CD-ROM 3501, the FD 3502, or the network.

  The program does not necessarily include an operating system (OS) or a third-party program that causes the computer 341 to execute functions such as the brain activity information output device according to the above-described embodiment. The program only needs to include an instruction portion that calls an appropriate function (module) in a controlled manner and obtains a desired result. How the computer system 340 operates is well known and will not be described in detail.

  In the above program, in the transmission step for transmitting information, the reception step for receiving information, etc., processing performed by hardware, for example, processing performed by a modem or an interface card in the transmission step (only performed by hardware). Not included) is not included.

  Further, the computer that executes the program may be singular or plural. That is, centralized processing may be performed, or distributed processing may be performed.

  In each of the above embodiments, each process (each function) may be realized by centralized processing by a single device (system), or by distributed processing by a plurality of devices. May be.

  The present invention is not limited to the above-described embodiments, and various modifications are possible, and it goes without saying that these are also included in the scope of the present invention.

  As described above, the brain activity information output device according to the present invention has an effect that it can output information on brain activity with high accuracy, and is useful as a brain activity information output device or the like.

Block diagram of brain activity information output system in Embodiment 1 Flow chart explaining the operation of the brain activity information output system The figure which shows the comparison of the MEG waveform before and after the same artifact removal The figure which shows the deviation from the average with the method which uses the same observation value, PCA and VBMEG Diagram showing time waveform and spatial map of the estimated current The figure which shows the difference in the estimation result with the presence or absence of the expansion dipole Overview of the computer system Block diagram of the computer system

Explanation of symbols

DESCRIPTION OF SYMBOLS 11 Brain signal measuring device 12 Brain activity information output device 121 Measurement brain signal information storage part 122 Brain prior information storage part 123 Artifact prior information storage part 124 Brain activity information acquisition part 125 Artifact information acquisition part 126 Output brain activity information acquisition part 127 Noise Removal accuracy information acquisition unit 128 Output unit

Claims (10)

A measurement brain signal information storage unit capable of storing measurement brain signal information, which is information about the measured brain signals;
A brain advance information storage unit capable of storing brain advance information that is advance information related to brain activity;
An artifact advance information storage unit that can store one or more artifact advance information that is advance information on an artifact source;
Using the measurement brain signal information and the brain prior information, a brain activity information acquisition unit that estimates and acquires brain activity information that is information of brain activity;
An artifact information acquisition unit that estimates and acquires one or more artifact information that is information of an artifact source using the measurement brain signal information and the one or more artifact prior information;
Using the measured brain signal information, the brain activity information, and the one or more artifact information, a process for removing the influence of the artifact from the measured brain signal information is performed. An output brain activity information acquisition unit for acquiring
A brain activity information output device comprising: an output unit that outputs the output brain activity information. The artifact prior information storage unit is
Stores multiple artifact prior information,
The artifact information acquisition unit
Estimate artifact information for multiple artifact sources, obtain multiple artifact information,
The output brain activity information acquisition unit
Using the measured brain signal information, the brain activity information, and the plurality of artifact information, a process for removing the influence of the plurality of artifacts from the measured brain signal information is performed, and an output brain activity that is information of the brain activity that is output The brain activity information output device according to claim 1 which acquires information. The brain prior information and the one or more artifact prior information are:
Including strength information, which is information about the strength of the signal,
3. The brain activity information output device according to claim 1, wherein the intensity information of the brain prior information and the intensity information of the one or more pieces of artifact prior information are different. The one or more artifact prior information is:
The brain activity information output device according to any one of claims 1 to 3, comprising biological artifact advance information that is advance information related to an artifact source included in a subject's living body. The one or more artifact prior information is:
The brain activity information output device according to claim 4, comprising external artifact advance information that is advance information related to an external artifact source not included in the subject's living body. The brain prior information is
fMRI intensity information is current distribution, and is a prior distribution representing prior knowledge about the current distribution,
The one or more pieces of artifact prior information are:
a prior distribution that uses a large current dispersion compared to the fMRI intensity information and represents prior knowledge of the current distribution;
The brain activity information acquisition unit
Estimating and obtaining brain activity information that is information about current at a plurality of dipole positions using hierarchical Bayesian estimation using the measured brain signal information and the brain prior information,
The artifact information acquisition unit
Estimating and obtaining one or more artifact information, which is information about the current at the dipole position of the artifact source, using hierarchical Bayesian estimation using the measured brain signal information and the one or more artifact prior information;
The output brain activity information acquisition unit
From the measured brain signal information, the brain activity information corresponding to a dipole arranged at a position considered to have no brain activity in the brain activity information and the artifact information are removed, and output brain activity information is obtained. The brain activity information output device according to any one of claims 1 to 5, which is acquired. The measured brain signal information is:
Information about the magnetic field observed around the head,
The output brain activity information acquisition unit
Obtaining background brain magnetic field information, which is information related to a magnetic field, from current information, which is brain activity information corresponding to a dipole arranged at a position considered to have no brain activity in the brain activity information, and the artifact Obtain the artifact magnetic field information that is information about the magnetic field from the current information that is information,
The brain activity information output device according to any one of claims 1 to 6, wherein processing for removing the background brain magnetic field information and the artifact magnetic field information is performed from the measured brain signal information to obtain output brain activity information. Using the output brain activity information acquired by the output brain activity information acquisition unit and the measured brain signal information, noise removal accuracy for acquiring noise removal accuracy information that is information related to noise removal accuracy in the output brain activity information It further comprises an information acquisition unit,
The output unit is
The brain activity information output device according to any one of claims 1 to 7, wherein the output brain activity information is output only when the noise removal accuracy information is higher in accuracy than a threshold value stored in advance. A brain activity information output unit realized by a brain activity information acquisition unit, an artifact information acquisition unit, an output brain activity information acquisition unit, and an output unit,
The brain activity information acquisition unit estimates and acquires brain activity information, which is information of brain activity, using the measured brain signal information and brain prior information stored in a storage medium;
Artifacts obtained by estimating and acquiring one or more artifact information, which is information of an artifact source, using the measured brain signal information and one or more artifact prior information stored in a storage medium by the artifact information acquisition unit An information acquisition step;
The output brain activity information acquisition unit performs processing for removing the influence of the artifact from the measured brain signal information using the measured brain signal information, the brain activity information, and the one or more artifact information, and is output to the brain An output brain activity information acquisition step for acquiring output brain activity information which is information of the activity;
A brain activity information output method comprising: an output step of outputting the output brain activity information by the output unit. Computer
A brain activity information acquisition unit that estimates and acquires brain activity information that is information of brain activity using the measured brain signal information and brain prior information stored in the storage medium;
An artifact information acquisition unit that estimates and acquires one or more artifact information that is information of an artifact source using the measurement brain signal information and one or more artifact prior information stored in a storage medium;
Using the measured brain signal information, the brain activity information, and the one or more artifact information, a process for removing the influence of the artifact from the measured brain signal information is performed. An output brain activity information acquisition unit for acquiring
A program for functioning as an output unit for outputting the output brain activity information.